Have you ever dreamed of being able to visually explore your data? If you have, Qlik is your dream come true. Qlik, and in particular Qlik Sense, allows you to perform data discovery on just about any data set with relative ease. In this post, I am going to walk you through my favorite way let Qlik help you create valid relationships between tables in an unfamiliar data set. All told, this article should take 5 minutes to read, and less than 30 minutes if you are following along with the actual Qlik app.

Qlik’s First Question: to Add Data or Not to Add Data

Whenever you create a new Qlik application, you are presented with an option of “Add Data” and “Data load editor.”

The way I think about these differences is that “Add data” is easy, and “Data load editor” is for people who enjoy punishment (they will claim that they prefer greater control over the import process). Both approaches have their strengths, but if you are just looking to jump in with both feet and start exploring your data, I would start with Add data.

If you want to play with a simple dataset, you can download this Excel file that I created to demonstrate some of the fundamentals of adding data to Qlik Sense. I will be using this data for the rest of this post.

Associate Data in Qlik Sense

After you add data, you are going to be slapped in the face with a simple truth: Qlik Sense, which allows you to bring visual meaning to very complex data, has some very complex user interface (Qlik is radically improving this in Qlik Sense 3!). Unless you are just dealing with a single set of data, the first thing you need to do after adding data is associate the data you added. Here is a screen shot that you are presented with…do you see how to create the relationships between your data? Of course you do! It is that little tiny “Associations” button at the bottom of the screen. 🙂

Once you have clicked on the Associations tab, you are presented with an option to associate each of the tables together. For each table to table relationship (e.g., Customers – Theaters), you need to select either “No Association” or one of the recommended associations. For the Customers – Theaters combination, there is no relationship, so you select “No Association” and then select the down arrow to advance to the next table.

NOTE ABOUT OVER-JOINING: Notice how Qlik recommends the association between Customer and Theater with 100% confidence. There is no relationship between customers and theaters (a person can purchase a ticket at any theater, and the only proper relationship is through the purchase entity). But, because Customer and Theater both have a city field and these have the same values, Qlik recommends a relationship 100%. I still love Qlik for recommending these joins, because it is a lot easier to see a recommendation and determine that it is invalid than having to try to imagine what relationships might exist – particularly on a large and complex data model.

Now that we advance to the Purchases – Theaters table, we see some pretty amazing smarts on display by Qlik: we have the purchaser’s name as “name” and the theater’s name as “name” – but a person’s name (e.g., Matt) is not the same as a theater’s name (e.g., Regal 8). Qlik recognizes that the proper join is between Purchase.Theater and Theater.Name and suggests this association with 100% confidence.

After you go through all of the possible associations, you should have a pretty good object model.

And if you switch over to the Data Load Editor, you will see a nice clean script that Qlik created for your data.